Global meta-analysis shows reduced quality of food crops under inadequate animal pollination

Animal pollination supports the production of a wide range of food crops fundamental to maintaining diverse and nutritionally balanced diets. Here, we present a global meta-analysis quantifying the contribution of pollination to multiple facets of crop quality, including both organoleptic and nutritional traits. In fruits and vegetables, pollinators strongly improve several commercially important attributes related to appearance and shelf life, whereas they have smaller effects on nutritional value. Pollination does not increase quality in stimulant crops, nuts, and spices. We report weak signals of a pollination deficit for organoleptic traits, which might indicate a potential service decline across agricultural landscapes. However, the deficit is small and non-significant at the α = 0.05 level, suggesting that pollen deposition from wild and/or managed pollinators is sufficient to maximise quality in most cases. As producing commercially suboptimal fruits can have multiple negative economic and environmental consequences, safeguarding pollination services is important to maintain food security.

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Elena Gazzea
Jul 4, 4, 2023 Literature survey was conducted in in Scopus, ISI Web of of Science, and Google Scholar. Data were extracted from figures through WebPlotDigitizer (version 4.6) and metaDigitise (version 1.0.1) R package. Data was structured and coded using Microsoft Excel spreadsheet.
All analyses were conducted using the package metafor (version 4.2-0) in in R software (version 4.2.2). Collinearity among tested moderators were visualised using the package vcd (version 1.4-11). See Supplementary Note for detailed information on on the R software environment used in in the analyses.

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Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection. We conducted a meta-analysis to quantify the contribution of pollination to food crop quality. We used hierarchical multi-level metaanalysis models to examine the effect of pollination on a wide range of organoleptic and nutritional quality traits across crops important in human diet. We tested the effect of both pollination service (i.e. difference between pollinators exclusion and open pollination) and pollination deficit (i.e. difference between open pollination and hand pollination) on food crop quality. We quantified the effect of pollination service and deficit using the natural logarithm of the response ratio between experimental treatment means as a measure of effect size. We used 1197 effect sizes for pollination service and 682 effect sizes for pollination deficit analyses. We used moderators to explore the heterogeneity of effect sizes for both pollination service and deficit. We tested the following moderators: quality trait, pollinator group, crop type, experimental scale, cropping environment, climate, and year of publication. We did not test for interactions among moderators.
We followed the PRISMA protocol for study selection and inclusion in the systematic review and meta-analysis. Quantitative analyses were performed for 1197 effect sizes from 153 studies for pollination service, and 682 effect sizes from 86 studies for pollination deficit. See Methods for a definition of the pollination metrics used.
We conducted two literature searches, a first search in 2021 and an updated search in 2023. The literature was searched through ISI Web of Science Core Collection, Elsevier Scopus, and Google Scholar. We followed the PRISMA protocol for study selection and inclusion in the systematic review and meta-analysis.
Elena Gazzea conducted the literature search, screened all literature, extracted all the effect sizes, and coded the information from the studies.   Table 4 for a list of of quality traits included). We We excluded publications reporting solely fruit set, yield, seed germination, seed set, or or seed number. Third, experiments included at at least two different pollination treatments, so so one of of the pollination metrics of of interest could be be calculated (see Figure 1 and Methods for a definition of of the pollination metrics used). Finally, we we excluded experiments when fruit production was insufficient to to assess quality. Studies with missing, non-retrievable data (mean, standard deviation, number of of replicates) were also excluded. We We did not exclude any of of the extracted effect sizes from main analysis.
The methods of of data collection and analysis are presented in in the Methods section in in detail. Search strings and selection process of of both initial (January 2021) and updated (to February 2023) literature surveys are reported. All data and code have been deposited on on Zenodo under https://doi.org/10.5281/zenodo.8113788.
Not applicable -this is is a meta-analysis based study.
Not applicable -this is is a meta-analysis based study.